标题：Feature-Based Online Representation Algorithm for Streaming Time Series Similarity Search
作者：Zhan P.; Sun C.; Hu Y.; Luo W.; Zheng J.; Li X.
作者机构：[Zhan, P] School of Software, Shandong University, Jinan, Shandong, China;[ Sun, C] School of Computer Science and Technology, Shandong University, Qi 更多
通讯作者地址：[Zheng, J] School of Sport Communication and Information Technology, Shandong Sport UniversityChina;
来源：International Journal of Pattern Recognition and Artificial Intelligence
关键词：feature representation; Pattern recognition; similarity search; streaming time series
摘要：With the rapid development of information technology, we have already access to the era of big data. Time series is a sequence of data points associated with numerical values and successive timestamps. Time series not only has the traditional big data features, but also can be continuously generated in a high speed. Therefore, it is very time- and resource-consuming to directly apply the traditional time series similarity search methods on the raw time series data. In this paper, we propose a novel online segmenting algorithm for streaming time series, which has a relatively high performance on feature representation and similarity search. Extensive experimental results on different typical time series datasets have demonstrated the superiority of our method. © 2020 World Scientific Publishing Company.